Some Thoughts on HFIP. Bob Gall

Transcription

1 Some Thoughts on HFIP Bob Gall

2 Thanks! For putting up with me for the last six years, For helping to create a Hurricane Project that I believe has been very successful I will be mostly retiring at the end of the year Vijay will be taking over as Development Director Rather than the usual outline of HFIP technical achievements in the past year much of which you will hear from the team reports-- I thought I would outline some of my thoughts and comments about HFIP

3 Reasons for the success of HFIP It had significant funding you can t make much happen without sufficient resources It brought together a broad community -- research to development to operational implementation to work collectively on the hurricane problem. It facilitated communication within a large group Bi-Weekly telecons, annual meeting, workshops Community participation is developing project plans the teams It developed facilities DTC for code access and testing provides basic link R2O A dedicated large computer facility The community effort allowed a large group of scientists to focus on a single problem

4 Some general Comments Initialization remains HFIP s biggest problem Don t ignore the global model A question about statistical significance Don t ignore Ensembles More community focus on developing physics packages Comments on Recent HFIP Performance

5 Don t ignore the global model You will hear a recommendation from the SRC to cease any focus on the global model problem I am not sure that is good advice SRC feels we should focus on initialization/physics and the first 1-3 days focus on the regional model But the global model is still a central part of any regional system to the HFIP goals There is a sense within NOAA that the NGGPS project will take care of the global model But there problems/issues with the global models that are unique to the hurricane problem There needs to be some way to insure that they are appropriately addressed

6 The HFIP Project Vision/Goals Vision Organize the hurricane community to dramatically improve numerical forecast guidance to NHC in 5-10 years Goals Reduce numerical forecast errors in track and intensity by 20% in 5 years, 50% in 10 years Extend forecast guidance to 7 days with skill comparable to 5 days at project inception Increase probability of predicting rapid intensification at day 1 to 90% and 60% at day 5 6 6

7 NCEP vs ECMWF for Atlantic % gain over HFIP baseline (track) GFS ECMWF 7

8 NCEP vs ECMWF for Atlantic 2012 % gain over HFIP baseline (track) GFS ECMWF 8

9 The Initialization Problem There is no doubt that initialization remains a major problem for the program The problem pretty much eliminates the value of the regional model forecasts in the 0-2 day range (intensity) Forecasts of RI by a model during these first 2 days have little reliability The problem is likely mostly related to initial conditions that are inconsistent with the model dynamics/physics The initialization will likely ultimately be solved through data assimilation But the resultant initial flow will need to be model consistent somehow Improved data will help but it isn t the main problem

10 Stream 2.0 Skill (AL Intensity) - Smaller sample size - Decay SHIPS shows highest model skill APSI skill gain is largest through 72 h

11 Stream 1.5 Skill (AL Intensity) - Statisticaldynamical configurati ons show highest skill including SPC3 Dynamical models transition from (-) to (+) skill with lead time CXTI and UW4I show lowest skill

12 Stream 1.5 Skill (EP Intensity) - CXTI and HWFI show highest skill Statisticaldynamical configuratio ns generally lose skill with lead time HFIP 5-yr skill goal met intermittent ly

13 Question about statistical significance Recently there has been a lot of emphasis on looking at the statistical significance of error comparisons Such as the impact of some change compared to a control run There is no doubt that this is very important in some settings But note that almost all tests of the impact of some change in the model at NCEP are not statistically significant Yet they are used to make decisions on model changes And the models get better.

14 Impact of Radar Data

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17 Don t Ignore Ensembles I probably don t have to say this to ensemble people But they seem to want to focus on probabilities But most folks want to know when and where NHC thinks the hurricane is going to hit and how strong it will be when it does which is a deterministic forecast Ensembles give some information like that ensemble mean But we are throwing away a huge amount of information that can be used to improve a deterministic forecast from both multi-model and single ensembles. This isn t a criticism of forecasters It is a criticism of the project that hasn t put enough emphasis on developing simple tools for extracting this information from the ensemble and presenting them to the forecaster

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20 Emphasis on Physics Packages The two primary areas where we can improve the models is Initialization and improved physics packages In my opinion we need more focus within the broad community (outside the operational centers) on developing/testing/improving physics packages Particularly the university community I am not sure why physics gets less emphasis in the research community than say data assimilation (and cores)

21 Comments on Recent HFIP Performance

22 Operational Intensity Forecast Trends* and HFIP Goals *Courtesy NHC: 2013 results are preliminary, subject to revision

23 HWRF Intensity ATL Basin Cumulative Forecast Improvements Improving 15-20% per year since version is approaching 5 year goal 23

24 Stream 1.5 Skill (AL Intensity) - Statisticaldynamical configuratio ns show highest skill including SPC3 Dynamical models transition from (-) to (+) skill with lead time CXTI and UW4I show lowest skill most lead times

25 Stream 2.0 Skill (AL Intensity) - Smaller sample size - Decay SHIPS shows highest model skill APSI skill gain is largest through 72 h

26 Stream 1.5 Skill (AL Track) - GPMI lowest skill for most lead times, but still higher than HFIP 5-yr skill goal HWRF highest skill among operation al models

27 Stream 2.0 Skill (AL Track) - Smaller sample size HWRF and FIM configurati ons show highest skill most lead times HFIP 5-yr skill goal surpassed for most lead times